Video quality monitoring method, distribution server, and client

ABSTRACT

A video quality monitoring method includes a distribution server measuring first video quality index values according to a full-reference method by comparing a video, distributed from the distribution server to a client through a network, with a degraded video, generated by causing multiple scenarios of quality degradation due to the network in the video in a pseudo manner, creating characteristic data of first quality degradation values, obtained by causing the quality degradation to vary with the scenarios at regular intervals, and the first video quality index values corresponding to the respective scenarios, and transmitting the characteristic data to the client; and the client measuring a second quality degradation value in the video distributed through the network, and calculating a second video quality index value, equivalent to a value according to the full-reference method, of the distributed video from the measured second quality degradation value and the characteristic data.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application is a continuation application filed under 35 U.S.C.111(a) claiming benefit under 35 U.S.C. 120 and 365(c) of PCTInternational Application No. PCT/JP2007/066127, filed on Aug. 20, 2007,the entire contents of which are incorporated herein by reference.

FIELD

A certain aspect of the embodiments discussed herein is related to amethod of monitoring video quality, a distribution server, and a client.

BACKGROUND

Recent years have seen developments in video distribution services withan increase in the speed of Internet access lines, the emergence oftheir optical version, and increases in the capacities of the backbonesof carriers and Internet service providers (ISPs). ISPs and carriersregard video distribution services as services for differentiatingthemselves from others as well, and prepare contents with uniquefeatures to obtain users.

Further, coding techniques have made progress to allow video signals,which basically contain a large amount of information, to be compressedwhile maintaining their video quality, which may be considered asanother factor in the increase in these video services. Standards suchas MPEG-2, MPEG-4, and H.264 have made it possible to transmit videosignals in a relatively low frequency band of several Mbps to tens ofMbps, which has enabled simultaneous distribution of video to multipleusers.

Further, studies have been made of future IP redistribution of broadcastservices that distributes present broadcast services of terrestrialdigital broadcasting through IP networks. Thus, video services areexpected to become one of basic network services in the future.

SUMMARY

According to an aspect of the invention, a video quality monitoringmethod includes a distribution server measuring a plurality of firstvideo quality index values according to a full-reference method bycomparing a video, distributed from the distribution server to a clientthrough a network, with a degraded video, generated by causing aplurality of scenarios of quality degradation due to the network in thevideo in a pseudo manner; the distribution server creatingcharacteristic data of a plurality of first quality degradation values,obtained by causing the quality degradation to vary with the scenariosat regular intervals, and the first video quality index valuescorresponding to the respective scenarios, and transmitting thecharacteristic data to the client; the client measuring a second qualitydegradation value in the video distributed through the network; and theclient calculating a second video quality index value, equivalent to avalue according to the full-reference method, of the distributed videofrom the measured second quality degradation value and thecharacteristic data.

According to an aspect of the invention, a distribution serverconfigured to distribute a video to a client through a network includesa degraded video generation unit configured to generate a degraded videoby causing a plurality of scenarios of quality degradation due to thenetwork in the video in a pseudo manner; a video quality index valuemeasurement unit configured to measure a plurality of first videoquality index values according to a full-reference method by comparingthe video with the degraded video; a characteristic data creation unitconfigured to create characteristic data of a plurality of first qualitydegradation values, obtained by causing the quality degradation to varywith the scenarios at regular intervals, and the first video qualityindex values corresponding to the respective scenarios; and atransmission unit configured to transmit the characteristic data to oneof the client and a network management system connected to the network.

According to an aspect of the invention, a distribution serverconfigured to distribute a video to a client through a network includesa degraded video generation unit configured to generate a degraded videoby causing a plurality of scenarios of quality degradation due to thenetwork in the video in a pseudo manner; a video quality index valuemeasurement unit configured to measure a plurality of first videoquality index values according to a full-reference method by comparingthe video with the degraded video; a characteristic data creation unitconfigured to create characteristic data of a plurality of first qualitydegradation values, obtained by causing the quality degradation to varywith the scenarios at regular intervals, and the first video qualityindex values corresponding to the respective scenarios; and a videoquality index value calculation unit configured to receive a secondquality degradation value in the video measured and transmitted by theclient, and to calculate a second video quality index value, equivalentto a value according to the full-reference method, of the distributedvideo from the received measured second quality degradation value andthe characteristic data.

The object and advantages of the embodiments will be realized andattained by means of the elements and combinations particularly pointedout in the claims.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory and notrestrictive of the invention, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram illustrating a basic operation of a video qualitymonitoring method according to a first embodiment;

FIG. 2 is a diagram illustrating a basic operation of a video qualitymonitoring method according to a second embodiment;

FIG. 3 is a detailed block diagram illustrating a distribution serverand a client according to the first and second embodiments;

FIG. 4 is a functional diagram illustrating a configuration of an imagereception function unit according to the first and second embodiments;

FIG. 5 is a block diagram illustrating a functional configuration of acharacteristic data creation function unit according to the first andsecond embodiments;

FIG. 6 is a block diagram illustrating a functional configuration of anetwork quality characteristic measurement function unit according tothe first and second embodiments;

FIG. 7 is a diagram illustrating an RTP packet format according to thefirst and second embodiments;

FIG. 8 is a block diagram illustrating a functional configuration of avideo quality index calculation function unit according to the first andsecond embodiments;

FIG. 9 is a block diagram illustrating the distribution server and theclient according to a third embodiment;

FIG. 10 is a diagram illustrating a basic flow of processing by thedistribution server and the clients according to the third embodiment;

FIG. 11 is a diagram illustrating a method (sequential) of defining anetwork quality degradation scenario in the pseudo network function unitaccording to the third embodiment;

FIG. 12 is a diagram illustrating a method (parallel) of defining anetwork quality degradation scenario in the pseudo network function unitaccording to the third embodiment;

FIG. 13 is a flowchart illustrating a flow of processing by acharacteristic data creation function unit according to the thirdembodiment;

FIG. 14 is a diagram illustrating FR-method video quality index values(DSCQS values) in the case of sequentially executing network qualitydegradation scenarios according to the third embodiment;

FIG. 15 is a diagram illustrating FR-method video quality index values(DSCQS values) in the case of executing network quality degradationscenarios in parallel according to the third embodiment;

FIG. 16 is a graph illustrating correction of average video qualityindex values according to the third embodiment;

FIG. 17 is a graph illustrating a profile according to the thirdembodiment;

FIG. 18 is a graph illustrating linear least squares approximationaccording to the third embodiment; and

FIG. 19 is a diagram illustrating calculation of the video quality indexvalue of distributed video in a video quality index calculation functionunit according to the third embodiment.

DESCRIPTION OF EMBODIMENTS

However, the following problems are likely to occur in response tofuture full-scale implementation of network video distribution servicessuch as Video on Demand (VOD) and Internet Protocol television (IPTV).

That is, the Internet currently does not guarantee packet transfer(transmission) quality such as a band and delay (that is, on best effortdelivery), so that the occurrence of congestion or network equipmentfailure in the network affects video services and causes the degradationof their video quality. For example, the occurrence of a packet loss inthe network due to a router failure causes block noise in the videoreproduced on a screen on the user side, and may prevent the video fromappearing on the screen in the worst case.

If such a problem occurs, a network operator and/or a video serviceprovider is desired to immediately become aware of the occurrence of thefailure in the video service and to subsequently restore the service byspecifying the cause and solving the problem.

Further, in view of future IP redistribution of terrestrial digitalbroadcasting services, it is desirable for the network operator toconstantly monitor video quality and determine whether the video qualityis ensured in the case of providing broadcast services through thenetwork, because the network is desired to satisfy as high a qualitystandard as broadcasting.

Conventionally, there are roughly two types of quality evaluation(assessment) methods for evaluating video quality: subjective qualityevaluation and objective quality evaluation.

The subjective quality evaluation, which is for a man to evaluate thequality that she/he perceives, includes, for example, mean opinion score(MOS) value evaluation. According to this method, multiple usersactually observe a video sample and numerically evaluate its videoquality, and the evaluation results are averaged to serve as anevaluation index. Some specific subjective quality evaluation methodsare defined in, for example, ITU-R BT.500-11. Typical examples ofsubjective quality evaluation methods include the double-stimuluscontinuous quality-scale (DSCQS) method.

On the other hand, the objective quality evaluation is not for a man butfor a measuring apparatus to evaluate quality. For example, with respectto the evaluation of the audio quality of Voice over Internet Protocol(VoIP) or the like, objective evaluation indexes such as the R value(defined by ITU-T G.107) are well known. On the other hand, ITU-T J.144defines the following three kinds of evaluation approaches as objectivequality evaluation methods for video quality.

The full reference (FR) method evaluates the degree of video degradationby comparing degraded video (video subjected to quality degradation suchas a packet loss through a network in the case of network videodistribution services) and the original video.

The non reference (NR) method evaluates video using only degraded videowithout using original video. Since no original video is used, theproblems of the FR method do not occur. However, no specific evaluationmethods have been established yet.

The reduced reference (RR) method replaces the original video with itsfeature information for comparison with degraded video in the FR method.

Japanese Laid-open Patent Publication No. 2004-23115 disclosescalculating transmission characteristic parameters at the time of adigital data sequence into which media information such as audio andvideo has been encoded passing through a communication channel;providing a pseudo communication channel having the transmissioncharacteristics set by the transmission characteristic parameters; andreproducing the audio and video media information from the digital datasequence that has passed through the pseudo communication channel,thereby evaluating communication service quality after passage throughthe communication channel.

Japanese Laid-open Patent Publication No. 2005-229214 discloses a videoservice quality control method including performing a degradationpattern extraction operation to infer a degradation pattern from theconditions of a server, a network, and a terminal measured during aservice with respect to the pre-determined subjective quality evaluationcharacteristics of the occurrence pattern of quality degradation;calculating the subjective evaluation value characteristics of thedegradation pattern; and determining the degradation of the quality ofthe service based on the calculation result, wherein the qualitydegradation pattern is measured together with the calculation of thesubjective evaluation value characteristics of the degradation pattern,and the quality degradation is determined by calculating long-termsubjective evaluation values from the relationship between the obtainedquality degradation pattern and the subjective evaluation values andfrom the long-term variation characteristics of the subjectiveevaluation values.

If the FR method is to be applied to network video distributionservices, naturally, an evaluation apparatus is to be installed near avideo receiver, that is, on the side of a user who receives videoservices because the degraded video that has passed through the networkis to be compared with its original (original video). Further, theoriginal video to be compared with the degraded video is also to beretained on the user side.

This situation is accompanied by the following difficulties. That is,generally, a dedicated hardware item is used as a concrete evaluationapparatus according to the FR method. Examples of apparatuses forevaluating the MOS value, which is a video quality index, according tothe FR method include VP21H manufactured by K-WILL Corporation. Thisapparatus calculates the MOS value in real time in response to theinputting of an original image and a degraded image. However, it iscostly and impractical to provide each video service receiving user withsuch a hardware apparatus.

Further, in order to retain the original video on the user side, it isnecessary to provide an apparatus for retaining the original video (astorage device) on the user side or to deliver the original video inadvance to the user using a network provided separately from the videodistribution network and causing no degradation of quality, which isalso costly and impractical. Therefore, there is a problem in that it isnot practical to monitor video quality degradation according to the FRmethod.

One NR method technique that is currently under development is an MDI(Media Delivery Index, RFC4445) measurement, which calculates a videoquality evaluation index value from a packet loss rate in the networkwithout using the original video. However, there is a problem in thatthe MDI has low reliability as a video quality index value; that is, thecorrelation between the MDI and the MOS value, which is a subjectivequality index, is low so as to prevent accurate evaluation.

Compared with the FR method, the RR method may retain informationsmaller in amount than the original video information conventionallyused. However, the RR method requires an evaluation apparatus to beprovided on the user side, and does not substantially solve problems ofthe FR method.

To sum up, no video quality evaluation method has been established thatperforms accurate evaluation quickly at low cost. It is desirable tosolve this problem in order to monitor video quality and detect itsdegradation in network video distribution services to be fullyimplemented in the future.

According to one aspect of the invention, a video quality monitoringmethod, a distribution server, and a client are provided that allow thequality of the video viewed by a user in a network video distributionservice to be evaluated quickly at low cost.

Preferred embodiments of the present invention will be explained withreference to accompanying drawings.

According to one aspect of the invention, video quality evaluation isperformed that is a combination of an FR method and an NR method.Further, as a basic approach, a video quality evaluation methodcalculates the video quality index value at the time of certain networkquality characteristics by correlating the measurements (measuredvalues) of network characteristics (such as packet loss and delay) andthe actual measurement (measured value) of the video quality evaluationindex.

[a] First Embodiment

FIG. 1 is a diagram illustrating a basic operation of a video qualitymonitoring method according to a first embodiment. Referring to FIG. 1,a distribution server 10 includes a video distributor 11 thatdistributes video, a pseudo network function unit 12 that emulates anetwork for actually distributing the video, a video quality evaluationfunction unit 13 that evaluates video quality, and a characteristic datacreation function unit 14A.

The video distributor 11 is supplied with video data fed from a videostorage device or a camera, and converts the video data into videotraffic. The video distributor 11 transmits the video traffic to acommunication network 20 and at the same time feeds the video traffic tothe pseudo network function unit 12 and the video quality evaluationfunction unit 13.

The pseudo network function unit 12 emulates a scenario of actualquality degradation by the communication network 20. The pseudo networkfunction unit 12 periodically varies the packet loss rate and delay atregular intervals, and supplies the video traffic degraded here bypacket loss to the video quality evaluation function unit 13. Further,the pseudo network function unit 12 supplies network qualitycharacteristic values such as a packet loss rate to the characteristicdata creation function unit 14A.

The degraded video traffic output by the pseudo network function unit 12may be supplied to a network quality characteristic measurement functionunit (having the same configuration as a network quality characteristicmeasurement function unit 31 described below) (not graphicallyillustrated), where network quality characteristic values such as apacket loss rate are measured to be supplied to the characteristic datacreation function unit 14A.

The video quality evaluation function unit 13 evaluates video quality,according to the FR method, from (based on) a video signal (referencevideo) obtained from the video traffic supplied from the videodistributor 11 and a video signal (degraded video) obtained from thevideo traffic degraded by a packet loss rate and delay in the pseudonetwork function unit 12, thereby measuring a video quality evaluationindex value at regular intervals, and supplies the measured videoquality evaluation index value to the characteristic data creationfunction unit 14A.

The characteristic data creation function unit 14A creates a profilethat is data on the correspondence between the network qualitycharacteristic values and the video quality evaluation index value on aregular interval basis, and transmits the created profile to a videoquality index calculation function unit 32A of one or more clients 30(only one of which is illustrated in FIG. 1 by way of example) throughthe communication network 20.

The client 30 includes the network quality characteristic measurementfunction unit 31, the video quality index calculation function unit 32A,and a client terminal 33. The client 30 evaluates the quality of videoreceived by a user based on the NR method. That is, the client 30 doesnot use original video but uses only degraded video for evaluation ofvideo quality.

The network quality characteristic measurement function unit 31 measuresa packet loss rate, which is an actual network quality characteristicvalue, of the video traffic received from the distribution server 10through the communication network 20, and transmits the measured valueto the video quality index calculation function unit 32A. Further, thenetwork quality characteristic measurement function unit 31 supplies theclient terminal 33 with the received video traffic.

The video quality index calculation function unit 32A calculates a videoquality index value according to the FR method on the client side atthat point from the measured network quality characteristic value andthe profile transmitted from the characteristic data creation functionunit 14A of the distribution server 10. Further, the video quality indexcalculation function unit 32A has a threshold for determining whetherthe video quality has degraded with respect to the calculated videoquality index value. If the calculated video quality index value exceedsthe threshold, the video quality index calculation function unit 32Adetermines that the quality of the video that is being viewed by a userhas degraded, and transmits alarm information to a network managementsystem 40 such as an NMS (network management system) managed by anetwork operator.

With the above-described process, it is possible to calculate a videoquality evaluation index value with accuracy based on the networkquality characteristic values measured in the client 30, and toimmediately notify the network management system 40 of the degradationof video quality.

Here, the distribution server 10 creates a profile at regular intervalsand transmits the created profile to the video quality index calculationfunction unit 32A of the client 30 for the following reason.

The video quality perceived by a user (perceived quality) with respectto a certain packet loss differs depending on the kind of a content or ascene of video. For example, with respect to an MPEG-2-encoded video, ascene that takes up the entire screen with a large object of the samecolor and a scene where multiple objects of various colors are disposedare compared. It is assumed that a packet loss occurs to cause blocknoise. In the former scene, the block noise blends with a background ofthe same color and does not stand out so much. Therefore, the perceivedquality is not so poor. On the other hand, in the latter scene, theblock noise is seen superposed on objects of various colors, so that thequality is perceived to be poor.

That is, the profile (the relationship between network qualitycharacteristic values such as a packet loss rate and a video qualityindex value), created in a certain time period during the playback(reproduction) of video by the distribution server 10, varies because ofa difference between scenes, time periods, or contents.

Therefore, according to this embodiment, a profile is created at regularintervals on the distribution server 10 side, and is transmitted to theclient 30 side every time the profile is created, thereby making itpossible to follow variations in video characteristics. On the client 30side, it is possible to accurately evaluate a scene that is being viewedby a user on the client terminal 33 by evaluating video quality usingthe (updated) profile transmitted at regular intervals, which is alwaysthe latest.

In the above-described basic operation, the profile generated at regularintervals in the distribution server 10 is transmitted to the client 30,and the client 30 calculates a video quality index value using actuallymeasured network quality characteristic values such as a packet lossrate and the profile. It is not always necessary, however, to calculatethe video quality index value in the client 30.

[b] Second Embodiment

FIG. 2 is a diagram illustrating a basic operation of a video qualitymonitoring method according to a second embodiment. According to thisembodiment, the profile information created by the characteristic datacreating function unit 14A of the distribution server 10 is nottransmitted to the client 30, and one or more network qualitycharacteristic values measured by the network quality characteristicmeasurement unit 31 of the client 30 are transmitted to the distributionserver 10 at regular intervals, so that a video quality indexcalculation function unit 15 provided in the distribution server 10calculates the video quality index value of the client 30 at regularintervals.

Therefore, while the video quality index calculation function unit 32A,which receives profile information and calculates a video quality indexvalue from measured network quality characteristic values, is providedin the client 30 in FIG. 1, the video quality index calculation functionunit 15 is provided subsequently to the characteristic data creatingfunction unit 14A of the distribution server 10 in FIG. 2.

The client 30 (or each client 30) transmits the network qualitycharacteristic values measured in the network quality characteristicmeasurement function unit 31 to the video quality index calculation unit15 of the distribution server 10 at regular intervals.

The video quality index calculation function unit 15 calculates a videoquality index value at that point based on the profile informationreceived at regular intervals from the characteristic data creationfunction unit 14A and the received network quality characteristicvalues.

Further, the video quality index calculation function unit 15 has athreshold for determining whether the video quality has degraded withrespect to the calculated video quality index value. If the calculatedvideo quality index value exceeds the threshold, the video quality indexcalculation function unit 15 determines that the quality of the videothat is being viewed by a user has degraded, and transmits alarminformation to the network management system 40 such as an NMS managedby a network operator.

The first embodiment and the second embodiment may be combined to alloweach of the distribution server 10 and the client 30 to calculate avideo quality index value.

Alternatively, the video quality index calculation function unit 15 maybe provided in the network management system 40. In this case, theprofile information created in the characteristic data creation functionunit 14A of the distribution server may be transmitted to the networkmanagement system 40 at regular intervals, and one or more networkquality characteristic values measured in the network qualitycharacteristic measurement function unit 31 of the client 30 may betransmitted to the network management system 40 at regular intervals, sothat the video quality index calculation function unit 15 provided inthe network management system 40 may determine the degradation of videoquality.

Next, a description is given of advance distribution of profileinformation.

In the above-described first and second embodiments, the distributionserver 10 creates a profile and distributes the profile to the clients30 at the same time as actual video distribution to users. In the caseof live distribution or live broadcasting, it is desirable to create aprofile at the same time as the distribution of video. In the case ofdistributing a content whose contents are known in advance, such as amovie or drama, a profile may be created in advance for the content tobe distributed, and the created profile may be provided to the videoquality index calculation function unit 15 or 32A before distribution ofthe content.

Next, a description is given in more detail of the distribution server10 and the client 30 in the first and second embodiments.

FIG. 3 is a detailed block diagram illustrating the distribution server10 and the client 30 in the first and second embodiments. FIG. 3 isbased on the video quality monitoring method of FIG. 1 according to thefirst embodiment.

Referring to FIG. 3, the video quality evaluation function unit 13 ofthe distribution server 10 includes an image reception function unit 13a, an image reception function unit 13 b, and an FR-type video qualityindex calculation function unit 13 c.

The image reception function units 13 a and 13 b convert the videotraffic supplied from the video distributor 11 and the video trafficsupplied from the pseudo network function unit 12, respectively, intovideo signals. For example, the image reception function units 13 a and13 b are implemented by a personal computer (PC) or the like, and outputvideo reproduced with video playback software on the PC, such as WindowsMedia Player or a VLC media player, as analog or digital video signals.

FIG. 4 is a functional diagram illustrating a configuration of the imagereception function unit 13 a. The image reception function unit 13 b mayhave the same configuration as the image reception function unit 13 a.Referring to FIG. 4, the image reception function unit 13 a (13 b)includes a packet reception unit 13-1, a video playback function unit13-2, and a video signal output unit 13-3. The packet reception unit13-1 is a network interface. Video packets (IP packets), which are videotraffic received by the packet reception unit 13-1, are reproduced byvideo playback software serving as the video playback function unit13-2, and are converted into and output as a video signal by the videosignal output unit 13-3 serving as a video processing function insidethe PC.

The video signal for original video generated in the image receptionfunction unit 13 a (reference video) and the video signal for degradedvideo generated in the image reception function unit 13 b (degradedvideo) are supplied to the FR-type video quality index calculationfunction unit 13 c.

As the FR-type video quality index calculation function unit 13 c, VP21Hmanufactured by K-WILL Corporation, which is a hardware-type videoquality evaluation apparatus, may be used, for example. The FR-typevideo quality index calculation function unit 13 c outputs, from (basedon) the reference video and the degraded video, a video quality indexcorresponding to a DSCQS value, which is a subjective evaluation index,as a video quality index value according to the FR method.

If the video signals output by the image reception function units 13 aand 13 b and video signals receivable by the FR-type video quality indexcalculation function unit 13 c are different in format, a video signalconverter (such as a scan converter) may be used.

Next, in the pseudo network function unit 12, a dedicated appliance forvarying one or more network quality characteristics in a pseudo manner,for example, for causing a packet loss or delay, may be used. Forexample, with respect to the packet loss rate, such an appliance has afunction of discarding passing IP packets at a specified packet lossrate during a specified period. The pseudo network function unit 12periodically discards passing IP packet at N kinds of different packetloss rates Ln at regular intervals Tp in order to emulate scenarios ofnetwork quality degradation. The specific values of the regular intervalTp, the number of kinds of packet loss values N (an integer greater thanone), and the packet loss rates Ln may be determined as network qualityscenarios from an external apparatus such as a PC, for example.Alternatively, the network quality scenarios may be specified byinternal configuration files. Further, the packet loss rates Ln may bespecified (determined) in ascending order, in descending order, or atrandom.

The characteristic data creation function unit 14A creates a profile bymapping the relationship between the video quality index values (DSCQSvalues) measured in the FR-type video quality index calculation unit 13c and the packet loss rates given in the pseudo network function unit12.

FIG. 5 is a block diagram illustrating a functional configuration of thecharacteristic data creation function unit 14A. Referring to FIG. 5, thecharacteristic data creation function unit 14A includes a video qualityindex value reception unit 14 a, a network quality characteristicinformation reception unit 14 b, a profile generation unit 14 c, and aprofile transmission unit 14 d.

The video quality index value reception unit 14 a receives video qualityindex values (DSCQS values) supplied from the FR-type video qualityindex calculation function unit 13 c at regular intervals. Then, thevideo quality index value reception unit 14 a transmits the receivedvideo quality index values directly to the profile generation unit 14 c,or averages the received video quality index values at predeterminedregular intervals and transmits the average of the video quality indexvalues to the profile generation unit 14 c.

The network quality characteristic information reception unit 14 breceives the values of the specified packet loss rates from the pseudonetwork function unit 12 (FIG. 3), and transmits the received values tothe profile generation unit 14 c.

The profile generation unit 14 c generates a profile by correlating theDSCQS values and the corresponding packet loss rates transmitted fromthe video quality index value reception unit 14 a and the networkquality characteristic information reception unit 14 b, respectively,for a certain period.

The profile generated in the profile generation unit 14 c is supplied tothe profile transmission unit 14 d. The profile transmission unit 14 dtransmits the supplied profile information to the video quality indexcalculation function unit 32A of the client 30 through the communicationnetwork 20 (FIG. 3).

The profile transmission unit 14 d may retain the profile information asa single file and transmit the profile information to the video qualityindex calculation function unit 32A of the client 30 by FTP (FileTransfer Protocol). Alternatively, the profile transmission unit 14 dmay transmit the profile information to a particular multicast address,and the video quality index calculation function unit 32A of the client30 may receive the profile information by being configured to receivefrom the multicast address. Further, the profile generation unit 14 cnotifies a received video switching control unit 16 (FIG. 3) of thedistribution server 10 of completion of the generation of the profile atthe same time that the profile generation unit 14 c transmits thegenerated profile to the profile transmission unit 14 d.

According to one aspect of the present invention, the received videowhose video quality is to be evaluated may be switched so that thequality of other video may be evaluated. Therefore, in response toreception of a profile generation completion notification from theprofile generation unit 14 c, the received video switching control unit16 instructs the image reception function units 13 a and 13 b (FIG. 3)to switch the received video to another one. This instruction is givenby, for example, indicating the reception address of the other video tothe image reception function units 13 a and 13 b. Specifically, forexample, if the distribution server 10 distributes video by multicast,the video to be received may be specified by specifying a multicastgroup (multicast address) to be received.

The received video switching control unit 16 may switch video to bereceived by, for example, prestoring the multicast addresses of videosto be subjected to video quality evaluation as a configuration file andspecifying a multicast address in accordance with the configuration filein response to reception of a profile generation completion notificationfrom the profile generation unit 14 c. The received video switchingcontrol unit 16 may be implemented with an apparatus such as a PC orimplemented in the same apparatus as the characteristic data creationfunction unit 14A.

Next, a description is given of evaluation of the quality of receivedvideo in the client 30. As illustrated in FIG. 3, for example, in theclient 30, the network quality characteristic measurement function unit31 precedes the client terminal 33, and measures one or more networkquality characteristic values of video traffic that is being received.

FIG. 6 is a block diagram illustrating a functional configuration of thenetwork quality characteristic measurement function unit 31. The networkquality characteristic measurement function unit 31 measures (detects),for example, packet loss. For example, a video stream is oftendistributed using RTP (Real-time Transport Protocol). Therefore, thediscarding of an RTP packet in the middle of a network may be determinedby observing an interruption of the sequence numbers of RTP packetheaders. FIG. 7 illustrates an RTP packet format. A packet of a videostream includes an IP (Internet Protocol) header 101, a UDP (UserDatagram Protocol) header 103, an RTP header 105, and an RTP payload 107for storing video information. The RTP header 105 includes the followingfields: V (Version) 201, P (Padding) 202, X (Extension) 203, CC (CSRC[Contributing Source] Count) 204, M (Marker) 205, PT (Payload Type) 206,Sequence Number 207, Timestamp 208, SSRC (Synchronization Source) 209(uniquely identifying the source of a stream), and CSRC 210 (identifyingcontributing sources to a stream). The sequence number is incremented byone for each RTP packet transmitted.

Referring back to FIG. 6, the network quality characteristic measurementfunction unit 31 includes a packet reception unit 31 a, a packetanalysis unit 31 b, a packet counting unit 31 c, and a network qualitycharacteristic calculation unit 31 d.

The packet reception unit 31 a receives a packet from the communicationnetwork 20 (FIG. 3), and supplies the received packet to the clientterminal 33. The packet reception unit 31 a also supplies the header ofthe received packet to the packet analysis unit 31 b.

The packet analysis unit 31 b analyzes the packet header, and determineswhether there is a lost or missing packet in RTP packet sequence. Thepacket analysis unit 31 b notifies the packet counting unit 31 c of thedetermination result. The packet counting unit 31 c counts the number oflost or missing packets (packets not received) in RTP packet sequence(the number of lost packets A) and the number of received packets B foreach pre-specified measurement period, and notifies the network qualitycharacteristic calculation unit 31 d of the number of lost packets A andthe number of received packets B counted.

The network quality characteristic calculation unit 31 d calculates apacket loss rate (%) for each pre-specified measurement period bydividing the number of lost packets A by the sum of the number of lostpackets A and the number of received packets B (A/(A+B)), and notifiesthe video quality index calculation function unit 32A (FIG. 3) of thecalculated packet loss rate (%).

FIG. 8 is a block diagram illustrating a functional configuration of thevideo quality index calculation function unit 32A. The video qualityindex calculation function unit 32A includes a profile informationreception unit 32 a, a network quality characteristic informationreception unit 32 b, a video quality index calculation unit 32 c, and athreshold determination unit 32 d.

The profile information reception unit 32 a receives a profile from thecharacteristic data creation function unit 14A of the distributionserver 10 (FIG. 3) at regular intervals, and updates the profile toconstantly retain the latest profile information. Further, the networkquality characteristic information reception unit 32 b receives a packetloss rate from the network quality characteristic calculation unit 31 dof the network quality characteristic measurement function unit 31 (FIG.6) at regular intervals.

The video quality index calculation unit 32 c calculates a video qualityindex value corresponding to the measured packet loss rate based on therelationship between the packet loss rate and the video quality indexvalue of the profile. This video quality index value is equivalent to anFR-method value obtained by the FR-method. The video quality indexcalculation unit 32 c transmits the calculated FR-method video qualityindex value to the threshold determination unit 32 d.

The threshold determination unit 32 d determines whether the videoquality index value exceeds a predetermined threshold. If the videoquality index value exceeds the threshold, the threshold determinationunit 32 d alerts the network management system 40 (FIG. 3). The networkmanagement system 40 may be alerted by the threshold determination unit32 d generating an alarm notification message and transmitting the alarmnotification message to the network management system 40 through thecommunication network 20.

Thus, since NR method-based video quality evaluation is performed in theclient 30, there is no need to retain original video or install astorage unit for retaining original video in the client 30. Further,there is no need to install such an expensive hardware-based videoevaluation apparatus as is employed in the FR method in each of theclients 30. On the other hand, an expensive hardware-based videoevaluation apparatus based on the FR method may be installed in thedistribution server 10 only. Accordingly, it is possible to implement avideo quality monitoring system including the distribution server 10 andthe multiple clients 30 (for example, FIG. 1 and FIG. 2) at low cost.

Further, according to one embodiment, the distribution server 10generates an accurate evaluation as a profile based on the FR-method,and the client 30 calculates a video quality index value using theprofile. This makes it possible to evaluate video quality with accuracy.

[c] Third Embodiment

A description is given of a distribution server and a client accordingto a third embodiment.

FIG. 9 is a block diagram illustrating the distribution server 10 andthe client 30 according to the third embodiment. In FIG. 9, the sameelements as those illustrated in FIG. 1 through FIG. 3 are referred toby the same reference numerals.

Referring to FIG. 9, the distribution server 10 includes the videodistributor 11, the pseudo network function unit 12 that emulates anetwork for actually distributing the video, the video qualityevaluation function unit 13 that evaluates video quality, and acharacteristic data creation function unit 14B.

The video distributor 11 is supplied with video data fed from a videostorage device or a camera, and converts the video data into videotraffic. The video distributor 11 transmits the video traffic to thecommunication network 20 and at the same time feeds the video traffic tothe pseudo network function unit 12 and the video quality evaluationfunction unit 13.

The pseudo network function unit 12 emulates the actual communicationnetwork 20 to periodically vary the packet loss rate and delay atregular intervals and supply the video traffic degraded here by packetloss to the video quality evaluation function unit 13. Further, thepseudo network function unit 12 supplies network quality characteristicvalues such as a packet loss rate to the characteristic data creationfunction unit 14B.

The video quality evaluation function unit 13 includes the imagereception function unit 13 a, the image reception function unit 13 b,and the FR-type video quality index calculation function unit 13 c.

The image reception function units 13 a and 13 b convert the videotraffic supplied from the video distributor 11 and the video trafficsupplied from the pseudo network function unit 12, respectively, intovideo signals. For example, the image reception function units 13 a and13 b are implemented by a personal computer (PC) or the like, and outputvideo reproduced with video playback software on the PC, such as WindowsMedia Player or a VLC media player, as analog or digital video signals.

As the FR-type video quality index calculation function unit 13 c, VP21Hmanufactured by K-WILL Corporation, which is a hardware-type videoquality evaluation apparatus, may be used, for example. The FR-typevideo quality index calculation function unit 13 c outputs, from (basedon) the reference video and the degraded video, a video quality indexcorresponding to a DSCQS value, which is a subjective evaluation index,as a video quality index value according to the FR method.

The characteristic data creation function unit 14B includes a videoquality index value correction unit 14 e, a measured value mappingfunction unit 14 f, a video quality index model creation unit 14 g, anda video index data transmission unit 14 h.

The video quality index value correction unit 14 e estimates the amountof impact of a video quality index value caused by the asynchronismphenomenon of the reference video and the degraded video output by theimage reception function units 13 a and 13 b, respectively, and correctsthe video quality index value by removing the estimated amount of impactfrom the video quality index value.

The measured value mapping function unit 14 f creates a profile bymapping the relationship between the video quality index value (DSCQSvalue) corrected by the video quality index value correction unit 14 eand the packet loss rate output by the pseudo network function unit 12with respect to the video received from the video distributor 11.

The video quality index model creation unit 14 g creates a video qualityindex model by approximating the tendency of the profile, which is dataon the correspondence between the packet loss rate of a network qualityscenario and a video quality index value (DSCQS value) obtained incorrespondence to the packet loss rate, to a function.

The video index data transmission unit 14 h transmits the generated(created) video quality index model to the network qualitycharacteristic measurement function unit 31 of the client 30 in responseto the completion of processing the distributed video by the videoquality index model creation unit 14 g.

FIG. 10 is a diagram illustrating a basic flow of processing by thedistribution server 10 and the clients 30. In FIG. 10, the multipleclients 30 may be collectively referred to in a singular form, that is,as “the client 30,” for convenience of description.

In step S1, the video distributor 11 receives a distribution video to bedistributed to the client 30.

In step S2, the pseudo network function unit 12 causes the distributionvideo to go through various scenarios of network quality degradationsuch as packet loss degradation.

In step S3, the characteristic data creation function unit 14B comparesthe distribution video received directly by the video quality evaluationfunction unit 13 (reference video) and the distribution video withnetwork quality degradation caused in a pseudo manner (degraded video),and measures a video quality index value (DSCQS value) from a differencein image quality between the reference video and the degraded video.

In step S4, the characteristic data creation function unit 14Bcorrelates the network quality scenarios executed in step S2 with thecorresponding video quality index values measured in step S3, and modelsthe tendency of changes in the correlation.

In step S5, the characteristic data creation function unit 14B transmitsthe video quality index model created in step S4 to a video qualityindex calculation function unit 32B of the client 30 (FIG. 9).

In step S6, the video quality index calculation function unit 32Bcalculates a video quality index value of the video that is beingdistributed to the client 30 by referring to the video quality indexmodel using the network quality measured in the network qualitycharacteristic measurement function unit 31. The calculated videoquality index value is equivalent to a FR-method value.

A description is given of defining a network quality degradationscenario according to this embodiment.

FIG. 11 and FIG. 12 are diagrams illustrating methods of defining anetwork quality degradation scenario in the pseudo network function unit12 according to this embodiment.

FIG. 11 illustrates a method of sequentially (serially) executingnetwork quality degradation scenarios. In FIG. 11, in a video qualityindex model creation interval of several seconds to several tens ofseconds, network quality degradation scenarios, that is, a packet lossrate of 0%, a packet loss rate of 0.5%, a packet loss rate of 1.0%, apacket loss rate of 1.5%, and a packet loss rate of 2.0%, aresequentially executed based on the assumption that scenes aresubstantially the same in video characteristics.

FIG. 12 illustrates a method of executing network quality degradationscenarios in parallel. In FIG. 12, network quality degradationscenarios, that is, a packet loss rate of 0%, a packet loss rate of0.5%, a packet loss rate of 1.0%, a packet loss rate of 1.5%, and apacket loss rate of 2.0%, are executed in parallel for the scene in avideo quality index model creation interval of several seconds toseveral tens of seconds.

Compared with the parallel scenarios, the sequential scenarios mayreduce the number of functional components (such as the pseudo networkfunction unit 12 and the video quality evaluation function unit 13) andtheir workloads. On the other hand, the parallel scenarios, which allowmultiple scenarios to be executed for a single scene so that theirevaluation scenes may be synchronized, allow video quality to beevaluated with high accuracy.

Next, a description is given of creation of characteristic data.

FIG. 13 illustrates a flow of processing by the characteristic datacreation function unit 14B.

In step S11, the average of FR video quality index values (DSCQS values)measured during execution of each network quality degradation scenariois determined.

In step S12, it is determined whether the average video quality indexvalue at the time of the scenario of a packet loss rate of 0% is in arange of normal values. If the average video quality index value at thetime of the scenario of a packet loss rate of 0% is not in a range ofnormal values (NO in step S12), in step S13, correction (filtering) isperformed, and the process proceeds to step S14. If the average videoquality index value at the time of the scenario of a packet loss rate of0% is in a range of normal values (YES in step S12), the processproceeds directly to step S14.

In step S13, the video quality index correction unit 14 e subtracts theaverage video quality index value in the scenario of a packet loss rateof 0% from each of the average video quality index values obtained inthe respective network quality degradation scenarios.

Here, the video quality index is supposed to always present a normalvalue (a DSCQS average of 0%) at the time of the scenario with nodegradation of network quality (a packet loss rate of 0%). An occurrenceof asynchronism between reference video and degraded video, however,prevents synchronization of video images, so that the video qualityindex presents an abnormal value (a DSCQS average greater than 0%). FIG.14 illustrates FR-method video quality index values (DSCQS values) inthe case of sequentially executing network quality degradationscenarios. FIG. 15 illustrates FR-method video quality index values(DSCQS values) in the case of executing network quality degradationscenarios in parallel.

At this point, attention is focused on the fact that the abnormal valuespresented by the video quality index are due to a factor other than thedegradation of network quality, and the average of the video qualityindex values indicating abnormality in spite of a good network qualityscenario (a packet loss rate of 0%) is calculated. Then, the averagevideo quality index values obtained at the times of the respectivenetwork quality degradation scenarios are corrected by removing thedifference between the average abnormal value and the correspondingnormal value, which difference is the average abnormal value itself,from each of the average video quality index values.

FIG. 16 illustrates correction of average video quality index values.Here, at the time of a packet loss rate of 0%, the average DSCQS value,which is G0 (abnormal value), minus 0 (normal value) equals G0(G0−0=G0). Further, if the average DSCQS value at the time of a packetloss rate of x % is Gx, Gx is corrected to Gx−G0.

In step S14, the measured value mapping function unit 14 f retains aprofile, which is data on the correspondence between the packet lossrates of the respective network quality degradation scenarios and thecorrected average video quality index values. FIG. 17 illustrates anexample profile.

In step S15, the video quality index model creation unit 14 g performslinear least squares approximation as illustrated in FIG. 18 in order tomodel the tendency of changes in the profile, that is, thecorrespondence data of the packet loss rate and the video quality indexvalue (average DSCQS value).

As a result of the liner least squares approximation, the followingformula is obtained:Video quality index value=a×packet loss rate+b,where a and b are function parameters.

This method takes advantage of a characteristic of the DSCQS value thatit presents linear changes relative to small variations in the packetloss rate.

In the case of using a DSCQS value as a video quality index value, thefunction parameter b is zero (b=0) because correction is performed instep S13. However, in the case of using video quality index values otherthan the DSCQS value, b may not be zero (b≠0). Accordingly, theparameters a and b are used. Further, the linear least squaresapproximation may be replaced with curve fitting. In this case, three ormore function parameters are employed.

In step S16, the video index data transmission unit 14 h transmits theparameters a and b to the video quality index calculation function unit32B of the client 30 (FIG. 9) with respect to the video quality indexmodel converted into a function (video quality index value=a×packet lossrate+b).

Next, a description is given of calculating the video quality indexvalue of distributed video.

The video quality index calculation function unit 32B receives theparameters a and b from the characteristic data creation function unit14B, and also receives a packet loss rate from the network qualitycharacteristic measurement function unit 31 at regular intervals.

The video quality index calculation function unit 32B calculates a videoquality index value corresponding to a measured packet loss rate basedon the following equation:Video quality index value=a×measured packet loss rate+b.

Further, the video quality index calculation function unit 32B has athreshold for determining whether the video quality has degraded withrespect to the calculated video quality index value. If the calculatedvideo quality index value exceeds the threshold, the video quality indexcalculation function unit 32B determines that the quality of the videothat is being viewed by a user has degraded, and transmits alarminformation to the network management system 40.

FIG. 19 illustrates calculation of the video quality index value ofdistributed video in the video quality index calculation function unit32B. Here, in order for “a scene subjected to evaluation at the time ofcreating a video quality index model” to be the same as “a scene wherethe video quality is estimated in a client (using the created videoquality index model),” a time (period) for creating a video qualityindex model is made equal to a period for measuring a packet loss rate.The calculation of a video quality index value in the client 30 isstarted in response to reception of video quality index data (functionparameters), that is, using reception of video quality index data as atrigger.

Thus, according to one aspect of the present invention, a function isprovided for automatically correlating one or more networkcharacteristics with a video quality index (a conventional index valueat an image level) for each of the scenes of distribution video, so thatit is possible to automatically construct a video quality index thatcannot be provided by the conventional evaluation method (that is, videoquality index values correlated with network quality in view of one ormore video scene characteristics).

Here, the FR-type video quality index calculation function unit 13 c(FIG. 9) obtains a DSCQS value that is an FR-type video quality indexfrom two kinds of input video, that is, reference video and degradedvideo. Therefore, it is desirable to evaluate these two kinds of videoin perfect synchronization. However, it is difficult to evaluate thereference video and the degraded video synchronously because of lack ofclock synchronization between functional components, for example.Further, the DSCQS value obtained from the reference video and thedegraded video varies greatly. However, according to this embodiment,the video quality index correction unit 14 e is provided so that it ispossible to obtain a profile where the relationship between the videoquality index value (DSCQS value) and the packet loss rate is accuratelymapped. Further, in place of the profile, the function parameters a andb are transmitted from the distribution server 10 to each of the clients30. Therefore, it is possible to reduce the traffic load of thecommunication network 20.

According to the above-described embodiments, the pseudo networkfunction unit 12 may be used as a degraded video generation unit, thevideo quality evaluation function unit 13 may be used as a video qualityindex value measurement unit, each of the characteristic data creationfunction units 14A and 14B may be used as a characteristic data creationunit, each of the characteristic data creation function unit 14A, thevideo index data transmission unit 14 h, and the quality characteristicmeasurement function unit 31 may be used as a transmission unit, thevideo quality index correction unit 14 e may be used as a correctionunit, the video quality index model creation unit 14 g may be used as afunction approximation unit, the network quality characteristicmeasurement unit 31 may be used as a quality degradation valuemeasurement unit, and each of the video quality index calculationfunction units 32A and 32B may be used as a video quality index valuecalculation unit and an alarm generation unit.

According to one aspect of the present invention, a video qualitymonitoring method includes a distribution server measuring a pluralityof first video quality index values according to a full-reference methodby comparing a video, distributed from the distribution server to aclient through a network, with a degraded video, generated by causing aplurality of scenarios of quality degradation due to the network in thevideo in a pseudo manner; the distribution server creatingcharacteristic data of a plurality of first quality degradation values,obtained by causing the quality degradation to vary with the scenariosat regular intervals, and the first video quality index valuescorresponding to the respective scenarios; the client measuring a secondquality degradation value in the video distributed through the network,and transmitting the measured second quality degradation value to thedistribution server; and the distribution server calculating a secondvideo quality index value, equivalent to a value according to thefull-reference method, of the distributed video from the transmittedmeasured second quality degradation value and the characteristic data.

According to one aspect of the present invention, a client configured toreceive a video distributed from a distribution server through a networkincludes a quality degradation value measurement unit configured tomeasure a quality degradation value in the video distributed through thenetwork; and a video quality index value calculation unit configured toreceive characteristic data transmitted from the distribution server atregular intervals and to calculate a video quality index value,equivalent to a value according to a full-reference method, of thedistributed video from the measured quality degradation value and thecharacteristic data.

The client as set forth above may further include an alarm generationunit configured to generate an alarm in response to the video qualityindex value calculated by the video quality index value calculation unitexceeding a threshold.

According to one aspect of the present invention, a client configured toreceive a video distributed from a distribution server through a networkincludes a quality degradation value measurement unit configured tomeasure a quality degradation value in the video distributed through thenetwork; and a transmission unit configured to transmit the measuredquality degradation value to one of the distribution server and anetwork management system connected to the network.

All examples and conditional language recited herein are intended forpedagogical purposes to aid the reader in understanding the inventionand the concepts contributed by the inventors to furthering the art, andare to be construed as being without limitation to such specificallyrecited examples and conditions, nor does the organization of suchexamples in the specification relate to a showing of the superiority orinferiority of the invention. Although the embodiments of the presentinventions have been described in detail, it should be understood thatvarious changes, substitutions, and alterations could be made heretowithout departing from the spirit and scope of the invention.

1. A video quality monitoring method, comprising: a distribution servermeasuring a plurality of first video quality index values according to afull-reference method by comparing a video, distributed from thedistribution server to a client through a network, with a degradedvideo, generated by causing a plurality of scenarios of qualitydegradation due to the network in the video in a pseudo manner; thedistribution server creating characteristic data of a plurality of firstquality degradation values, obtained by causing the quality degradationto vary with the scenarios at regular intervals, and the first videoquality index values corresponding to the respective scenarios, andtransmitting the characteristic data to the client; the client measuringa second quality degradation value in the video distributed through thenetwork; and the client calculating a second video quality index value,equivalent to a value according to the full-reference method, of thedistributed video from the measured second quality degradation value andthe characteristic data.
 2. The video quality monitoring method asclaimed in claim 1, wherein the distribution server creates thecharacteristic data before distributing the video to the client.
 3. Adistribution server configured to distribute a video to a client througha network, the distribution server comprising: a degraded videogeneration unit configured to generate a degraded video by causing aplurality of scenarios of quality degradation due to the network in thevideo in a pseudo manner; a video quality index value measurement unitconfigured to measure a plurality of first video quality index valuesaccording to a full-reference method by comparing the video with thedegraded video; a characteristic data creation unit configured to createcharacteristic data of a plurality of first quality degradation values,obtained by causing the quality degradation to vary with the scenariosat regular intervals, and the first video quality index valuescorresponding to the respective scenarios; and a transmission unitconfigured to transmit the characteristic data to one of the client anda network management system connected to the network.
 4. Thedistribution server as claimed in claim 3, wherein the characteristicdata creation unit includes: a correction unit configured to correct anaverage of the first video quality index values corresponding to one ofthe scenarios without the quality degradation to zero with respect to anaverage of the first video quality index values of each of the scenarioscorresponding to the respective first quality degradation values.
 5. Thedistribution server as claimed in claim 4, wherein the characteristicdata creation unit further includes: a function approximation unitconfigured to approximate data on a correspondence between the firstquality degradation values and the corrected averages of the first videoquality index values of the respective scenarios to a function, and todetermine a plurality of function parameters of the function as thecharacteristic data.
 6. The distribution server as claimed in claim 3,wherein the characteristic data creation unit is configured to determinea profile as the characteristic data, the profile being data on acorrespondence between the first quality degradation values and averagesof the first video quality index values of the respective scenarios. 7.The distribution server as claimed in claim 3, wherein the degradedvideo generation unit is configured to generate the degraded video byserially executing the scenarios of the quality degradation and causingthe quality degradation due to the network to vary with theserially-executed scenarios.
 8. The distribution server as claimed inclaim 3, wherein the degraded video generation unit is configured togenerate the degraded video by executing the scenarios of the qualitydegradation in parallel and causing the quality degradation due to thenetwork to vary with the scenarios executed in parallel.